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Data Scientist

Location: Peninsula (Redwood City)         posted: 06.27.24

Data Scientist, Electronic Arts, Inc., Redwood City, CA. Aggregate and analyze large and complex data sets to identify behavior trends using statistics, data mining, and machine learning techniques. Build prototype tools for investigating fraud events/behavior and analyzing system-wide trends. Research predictive modeling techniques and assist in developing business cases for new technologies needed to support fraud detection. Identify data sources. Use different tools such as SQL, Spark to extract data. Perform data cleaning. Analyze large data sets to identify behavior trends using statistics, data mining, and machine learning techniques. Use data mining techniques to compute KPI metrics. Develop algorithms and heuristics to identify fraudulent transactions and account creation, account compromises, and other high-risk activities. Extract data from various data sources. Partner with Engineering and Operations teams to define product requirements. Create centralized place and consistent definition for easier data Exchange. Build automated reports (e.g. Tableau), dashboards, and performance metrics. Being able to summarize the project into a story. Visualize the data to tell the story behind numbers and derive actionable insights for stakeholders and leadership. Automate the data report generation process. Telecommuting permitted. (E2-211167) 


40 hrs/week, Mon-Fri, 8:30 a.m. - 5:30 p.m. Salary Range From $151,736 to $204,700/yr. EA offers benefits incl PTO, medical/dental/vision insurance & 401(k) to eligible employees. Certain roles eligible for bonus & equity.




Master’s degree (or foreign equivalent) in Business Analytics, Mathematics, Statistics, Project Management or in a related field and three (3) years of experience in the job offered or in a data scientist-related occupation.


Position requires two (2) years of experience in each of the following skills:


· Fraud detection management to identify fraud trends, understand how to differentiate fraud behavior, know different fraud types and familiar with fraud detection tools;

· Using Python to build data quality framework, data pipelines and analytical models;

· Extract, transform and load data from various platforms through SQL queries;

· Build Machine Learning Models to improve and track performance to detect fraudulent activities;

· Using Spark to process data to perform tasks on very large data sets;

· Inspect, clean, transform and modeling data to discover useful information and dataset and to support decision making; and

· Work with business stakeholders, understand business requirements and convey the results of analytical research to non-technical audiences.


To apply, send resumes to and reference job code E2-211167. 

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